Accuracy in dietary assessment is essential for understanding the role of ingestive behavior in energy balance and chronic disease risk. Traditional and commonly used methods for assessing dietary intake, such as weighed or estimated food records, 24h recalls, and food frequency questionnaires all rely on self-report and are subject to reporting bias, particularly underreporting of energy intake. In this proposal, we describe a novel device for monitoring of food intake behavior, the Automatic Ingestion Monitor (AIM). The AIM has the potential to provide an accurate tool for monitoring of ingestive behavior by automatically detecting and capturing imagery of food intake. The AIM does not require any form of self-report from the user, only compliance with wearing the device. The AIM is simple to use and unobtrusive to daily activities; it can be worn for multiple days and only needs to be removed when bathing, showering or swimming. To our knowledge, no other monitoring technique has explored such an approach. The validation of the AIM system will be addressed in four specific aims: Specific Aim 1: Validate the AIM during ad-libitum food intake. Specific Aim 2: Implement semi-automatic energy density estimates from AIM-derived imagery. Specific Aim 3: Validate the accuracy of Total Energy Intake (TEI) measurement by the AIM2.0 in a community setting against doubly labeled water. Specific Aim 4: Identify the most cost-effective approach to analysis of AIM2.0 sensor and image data to accurately estimate energy intake.